Conda-python software development for diffuse nebulae photometry, optimized for the next generation telescope Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST)
LSST (https://www.lsst.org/about) is an astronomical observatory currently under construction in Chile with first light in 2023. It consists of an integrated system that combines an 8.4-meter primary mirror, the world’s largest digital camera (3200-megapixel) and a complex data processing system. Several research groups are currently working on the reduction pipelines (https://pipelines.lsst.io/index.htm) for the photometric data that LSST will allow to obtain.
Proposer will collaborate to optimize / implement techniques of extraction, calibration and flux measurement of galactic diffuse clouds, applying the effort to simulated LSST images. The trainee will work on the standard routines (https://github.com/lsst) developed in the conda-python Rubin common software environment (https://github.com/conda-forge/rubinenv-feedstock) for photometry of crowded field images.
The work will consist both in simulating LSST data (https://bitbucket.org/phosim/phosim_release/wiki/Home) and in the use and optimization of pipelines, on simulated data, for the extraction, calibration and measurement of galactic diffuse cloud flow, particularly in crowded fields.